GPT-5.5 on Oakgen: 1M Context, Native Reasoning, and What Changed from GPT-5.4

TL;DR

GPT-5.5 is now live on Oakgen. It is OpenAI's April 2026 refresh of the GPT-5.4 line — same 1.05M-token context, same price, but better reasoning, better tool reliability, and noticeably stronger recall on documents that push past 500K tokens. If you've been defaulting to GPT-5.4, switch.

You can pick GPT-5.5 from the model selector in Oakgen's chat or jump straight in: open it now.

What's actually new

GPT-5.5 keeps the architectural footprint of GPT-5.4 (dense transformer, multimodal in/out, native reasoning tokens) but ships three concrete improvements:

• Reasoning depth. Internal reasoning chains are longer and the model spends them more wisely. On math, code, and multi-step planning prompts, the difference shows up as fewer "I should double-check" hedges and more correct first answers.
• Long-context recall. GPT-5.4's recall above 500K tokens was patchy — names, numbers, and one-off facts got dropped. GPT-5.5 retrieves them reliably across the full 1.05M window.
• Tool-use reliability. Function-calling failures (malformed JSON, hallucinated tool names) drop noticeably. For agent stacks, that translates into fewer retry loops.

What did not change: pricing, max output tokens, vision support, or the OpenRouter model contract. It is a drop-in replacement at the API level.

GPT-5.5 vs GPT-5.4 head-to-head

Same money, more capability. That's the whole pitch.

When to use GPT-5.5

Long documents. If you regularly paste contracts, codebases, or research papers above 500K tokens, the recall improvement alone is worth the switch. GPT-5.4 would lose threads; GPT-5.5 keeps them.

Agent loops. Tool-use reliability compounds in multi-turn agents. A 2% reduction in malformed tool calls can mean 30% fewer end-to-end failures over a 10-step plan.

Reasoning-heavy chat. Math, code reviews, debugging sessions, technical writing edits — anywhere you'd previously have used GPT-5 (Thinking) or GPT-5.4 with high reasoning effort, GPT-5.5 narrows that gap and ships answers faster.

Vision + reasoning combined. Paste a chart or screenshot and ask a multi-step question. GPT-5.5's joint vision-and-reasoning trace is meaningfully tighter than 5.4's.

When GPT-5.4 (or another model) still makes sense

• Reproducibility. If you've pinned evals or production prompts to GPT-5.4's exact outputs, don't churn until you re-run your evals on 5.5.
• Cost-sensitive bulk text. For pure text reasoning at scale, Deepseek V4 Pro is still 60–80% cheaper. See our Deepseek V4 Pro vs GPT-5 comparison for the breakdown.
• Frontier vision. For pure visual reasoning (charts, screenshots), Claude Opus 4.7 and Gemini 3.1 Pro are competitive — try all three on your task.

Using GPT-5.5 via OpenRouter

The model ID is openai/gpt-5.5. A minimal streaming call looks like this:

import OpenAI from "openai";

const client = new OpenAI({
  apiKey: process.env.OPENROUTER_API_KEY,
  baseURL: "https://openrouter.ai/api/v1",
  defaultHeaders: {
    "HTTP-Referer": "https://oakgen.ai",
    "X-Title": "Oakgen.ai",
  },
});

const stream = await client.chat.completions.create({
  model: "openai/gpt-5.5",
  messages: [{ role: "user", content: "How many r's are in 'strawberry'?" }],
  stream: true,
});

for await (const chunk of stream) {
  const delta = chunk.choices[0]?.delta?.content;
  if (delta) process.stdout.write(delta);
  if (chunk.usage) {
    console.log("\nReasoning tokens:", chunk.usage.completion_tokens_details?.reasoning_tokens);
  }
}

Inside Oakgen, none of this matters — pick GPT-5.5 from the model selector in chat and the credits come out of the same pool you already use for every other model.

Try it on your own prompt

The honest test is your workload, not benchmarks. Open Oakgen chat, paste a prompt you've been running through GPT-5.4 or Claude Sonnet 4.6, and judge the output yourself. Switch models with one click, send the same prompt to a competitor, and compare.

For the wider LLM landscape, see our ChatGPT vs Claude vs Gemini vs Grok 2026 comparison.

Frequently asked questions

What is GPT-5.5 and how is it different from GPT-5.4? GPT-5.5 is the April 2026 successor. Same context window, same price, deeper reasoning, better long-context recall, and more reliable tool calling.

How much does GPT-5.5 cost on Oakgen? $2.50 per million input tokens, $15 per million output, $0.25 per million cached input — identical to GPT-5.4. Oakgen bills at 260 credits per USD with no markup.

Does GPT-5.5 support vision and tool use? Yes. Vision input, function calling, structured outputs, reasoning tokens, response_format, and seed are all supported.

What is the context window of GPT-5.5? 1,050,000 input tokens with up to 128,000 output tokens.

Should I switch from GPT-5.4 to GPT-5.5? For most users, yes — the price is the same and the model is better. Only stay if you have pinned evals against GPT-5.4's exact behavior.